DATA AND DATABASES VULNERABILITIES

The main focus of the learning in this knowledge module is to build an understanding of data and databases and giving meaning to data through data processing, analysis and visualisation

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Last updated Mon, 07-Aug-2023
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Course overview

The main focus of the learning in this knowledge module is to build an understanding of data and databases and giving meaning to data through data processing, analysis and visualisation

Requirements
  • NQF LEVEL 4
Curriculum for this course
65 Lessons 00:00:00 Hours
Course Overview
1 Lessons 00:00:00 Hours
  • Course Overview
    .
Data vulnerability and security
9 Lessons 00:00:00 Hours
  • Definition
    .
  • Data vulnerability, risk and exploitation
    .
  • Stages of data vulnerability: at network level, at system level, at data level.
    .
  • Process for protecting data
    .
  • Unauthorised access, elevation of privileges or denial of data
    .
  • What is a denial of service attack (DoS) ?
    .
  • Data corruption
    .
  • Data security solutions
    .
  • Formative Assessment
    .
Data and data processing
12 Lessons 00:00:00 Hours
  • Value of data
    .
  • Using RPA for Data Analytics
    .
  • Data sourcing:
    .
  • Refining data:
    .
  • Flaws in data:
    .
  • Frame of reference
    .
  • Limits of data acquisition
    .
  • Data:
    .
  • Data interactions,
    .
  • Assigned to different fields
    .
  • Why do we assign data types to fields?
    .
  • Formative Assessment
    .
Databases, data storage and access to data
20 Lessons 00:00:00 Hours
  • Data analysis for RPA: Importance of analysis
    .
  • Databases, data storage and access to data
    .
  • What is Structured Query Language (SQL)?
    .
  • Evolution of the database
    .
  • What’s the difference between a database and a spreadsheet?
    .
  • Types of databases
    .
  • What is database software?
    .
  • What is a database management system (DBMS)?
    .
  • What is a MySQL database?
    .
  • Using databases to improve business performance and decision-making
    .
  • Database challenges
    .
  • Data:
    .
  • Data
    .
  • Data Mining Concepts
    .
  • Relational database design
    .
  • Database design tools
    .
  • Create, design and modify relational database
    .
  • Import and export data
    .
  • Design and create queries
    .
  • Formative Assessment
    .
Structured query language (SQL)
3 Lessons 00:00:00 Hours
  • SQL programming language
    .
  • Storing, retrieving, managing or manipulating the data inside a relational database
    .
  • Formative Assessment
    .
Data scraping
8 Lessons 00:00:00 Hours
  • Concept and definition
    .
  • Purpose of data scraping
    .
  • Scraper bots can be designed for many purposes, such as:
    .
  • Data scraping tools
    .
  • Legal issues
    .
  • Web scraping procedure:
    .
  • Libraries used for web scraping
    .
  • Formative Assessment
    .
Software for analysing and visualising data.
11 Lessons 00:00:00 Hours
  • Reporting
    .
  • What is reporting in data visualization?
    .
  • Tables
    .
  • Pivot tables and pivot charts
    .
  • What is the benefit of using pivot tables and pivot charts?
    .
  • Dashboards
    .
  • Hierarchies and time data
    .
  • The data model
    .
  • Importing data from files
    .
  • Creating and formatting measures
    .
  • Visualizing data
    .
Final Assessment
1 Lessons 00:00:00 Hours
  • Summative Assessment
    .
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